The data is continuous (LDL values). The groups are "before" and "after" on the same patients.
Whether you are calculating the efficacy of a COVID-19 vaccine, determining the risk factors for diabetes in a cohort study, or simply trying to pass your final exam, Muhammad Ibrahim provides the roadmap. His work emphasizes that statistics is not about being "good at math"; it is about being honest with data. biostatistics by muhammad ibrahim
According to Ibrahim’s flow chart, this is a Paired T-test . The data is continuous (LDL values)
| Research Question | Type of Data | Suggested Test (Ibrahim’s Choice) | | :--- | :--- | :--- | | Compare means between 2 groups | Continuous, Normal | Independent T-test | | Compare means between 3+ groups | Continuous, Normal | ANOVA (Analysis of Variance) | | Compare proportions (e.g., cured vs. not cured) | Categorical | Chi-square (χ²) Test | | Measure strength of relationship | Continuous (Both variables) | Pearson Correlation | | Predict a disease outcome | Binary (Yes/No) | Logistic Regression | | Compare before/after treatment | Continuous, Paired | Paired T-test | His work emphasizes that statistics is not about